Data migration method and device, equipment and medium

Abstract

The invention discloses a data migration method and device, equipment and a medium, and relates to the technical field of distributed data storage. When a distributed database capacity reduction requirement exists, all to-be-migrated data in a source node is not directly migrated, related information of the to-be-migrated data is obtained, then migration parameters of all the to-be-migrated data are determined according to the related information, the migration parameters serve as data selection and migration bases, and whether the corresponding to-be-migrated data are allowed to be migrated or not is judged. Data selection can be accurately and effectively carried out based on migration parameters; if it is confirmed that the corresponding to-be-migrated data is allowed to be migrated, the to-be-migrated data is migrated from the source node to the target node, timely migration of important data is ensured, and the system performance is improved. And missing of important data or migration of unnecessary data is avoided, so that the system after capacity reduction can better meet business requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed data storage, and in particular to a data migration method, device, equipment and medium. Background Art

[0002] With the rapid advancement of information technology, the amount of data has increased dramatically. Distributed databases have been widely used in large-scale data processing scenarios due to their excellent scalability and high availability. Distributed databases are usually horizontally expanded according to business needs to improve storage and processing capabilities. However, business changes may lead to a decrease in data volume and load. At this time, maintaining the original large-scale distributed architecture will result in a waste of resources and increased costs.

[0003] To improve resource utilization and reduce costs, distributed databases need to scale down horizontally, that is, redistribute data and load to fewer nodes to adapt to business changes. Currently, horizontal scaling is mainly achieved through manual or simple rule-based data selection and migration. However, this data selection method is not smart enough, which may cause important data to fail to migrate in time or unnecessary data to be migrated, thus affecting system performance. For example, frequently accessed critical data may not be migrated first, resulting in a slower system response after scaling down.

[0004] In view of the above problems, how to solve the problem that the current method of data selection and migration in distributed databases is not intelligent enough, which may cause important data to fail to migrate in time or unnecessary data to be migrated, thereby affecting system performance, is an urgent problem to be solved by technical personnel in this field. Summary of the invention

[0005] The purpose of the present invention is to provide a data migration method, device, equipment and medium to solve the problem that the current data selection migration method in a distributed database is not intelligent enough, which may cause important data to fail to migrate in time or unnecessary data to be migrated, thereby affecting system performance.

[0006] In order to solve the above technical problems, the present invention provides a data migration method, comprising:

[0007] Obtain relevant information of each data to be migrated in the source node; wherein the relevant information at least includes access logs and attribute information;

[0008] Determine migration parameters of each of the data to be migrated according to the relevant information;

[0009] Determining whether to allow migration of the corresponding data to be migrated according to each migration parameter;

[0010] If so, the data to be migrated is migrated from the source node to the target node.

[0011] On the one hand, obtain relevant information of each data to be migrated in the source node, including:

[0012] Acquire the access time, accessor, access operation type and access content of the data to be migrated to obtain the access log of the data to be migrated; wherein the access operation type includes query operation, update operation and delete operation;

[0013] Acquire the creation time, modification time, data type, data size and business domain information of the data to be migrated to obtain the attribute information of the data to be migrated;

[0014] The access log and the attribute information are preprocessed to remove duplicate information in the access log and the attribute information, and to fill in missing information in the access log and the attribute information.

[0015] On the other hand, determining migration parameters of each of the to-be-migrated data respectively according to the relevant information includes:

[0016] Determine the access frequency, importance information and relevance information of each of the to-be-migrated data respectively according to the relevant information;

[0017] The access frequency represents the number of accesses to the data to be migrated per unit time; the importance information is the importance of the data to be migrated determined based on the business value of the data to be migrated, the access frequency and the update frequency; the correlation information represents the degree of association between the data to be migrated;

[0018] Correspondingly, judging whether to allow migration of the corresponding data to be migrated according to each migration parameter includes:

[0019] Whether to allow migration of the corresponding data to be migrated is determined according to at least one parameter among the access frequency, the importance information and the correlation information.

[0020] On the other hand, determining the access frequency of the data to be migrated includes:

[0021] Determine the data collection cycle;

[0022] Determine the number of times the data to be migrated is accessed within the data collection period;

[0023] The access frequency of the data to be migrated is determined according to the data collection cycle and the number of times the data to be migrated is accessed within the data collection cycle.

[0024] On the other hand, determining the importance information of the data to be migrated includes:

[0025] Determining the business value of the data to be migrated according to the creation time, the modification time, the data type, the data size and the business domain information of the data to be migrated;

[0026] Determining an update frequency of the data to be migrated according to the creation time and the modification time of the data to be migrated;

[0027] The importance information of the data to be migrated is determined according to the business value, the access frequency, and the update frequency of the data to be migrated.

[0028] On the other hand, determining the correlation information of the data to be migrated includes:

[0029] Obtaining observation values ​​of each of the data to be migrated respectively; wherein the observation values ​​are sample values ​​obtained by collecting the data to be migrated based on different conditions;

[0030] Determining the number of observations of each of the data to be migrated;

[0031] Determine the observed average value corresponding to each of the data to be migrated according to the observed value corresponding to each of the data to be migrated and the number of observed values;

[0032] The correlation information of each of the data to be migrated is determined according to the observed value, the number of observed values ​​and the observed average value of each of the data to be migrated.

[0033] On the other hand, judging whether to allow the corresponding data to be migrated to be migrated according to each migration parameter includes:

[0034] Determining whether the access frequency is not less than a first threshold, the importance information is not less than a second threshold, and the relevance information is not less than a third threshold;

[0035] If it is confirmed that the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the relevance information is not less than the third threshold, the corresponding data to be migrated is allowed to be migrated, otherwise the corresponding data to be migrated is not allowed to be migrated.

[0036] On the other hand, migrating the data to be migrated from the source node to the target node includes:

[0037] Obtaining the load of each node in the distributed database and obtaining the network bandwidth between each of the nodes;

[0038] Obtaining the data size of the data to be migrated;

[0039] Determining a migration path cost of each migration path of the data to be migrated according to the load of each node, the network bandwidth between each node, and the data size of the data to be migrated;

[0040] Determining a minimum migration path cost based on each of the migration path costs;

[0041] Determining the migration path corresponding to the minimum migration path cost as the target migration path;

[0042] A node corresponding to the target migration path is determined as the target node, and the data to be migrated is migrated from the source node to the target node through the target migration path.

[0043] On the other hand, it also includes:

[0044] Monitoring the performance index of the system processor during the migration of the data to be migrated through a preset command;

[0045] Monitoring the amount of data that has been migrated during the migration of the data to be migrated, and monitoring the amount of memory used and the network bandwidth used by the system during the migration of the data to be migrated;

[0046] Determine the quotient of the amount of migrated data and the total amount of data to be migrated and express it as a percentage to obtain the migration progress;

[0047] Determine the quotient of the used memory amount and the total memory amount and express it as a percentage to obtain memory usage;

[0048] Determine the quotient of the used network bandwidth and the total network bandwidth and express it as a percentage to obtain network bandwidth usage;

[0049] The migration progress, the memory usage and the network bandwidth usage are output.

[0050] On the other hand, it also includes:

[0051] When a network interruption is detected during the migration of the data to be migrated, determining whether the number of reconnections between the source node and the target node reaches a threshold;

[0052] If not, resend a connection request to the target node to reestablish the communication connection between the source node and the target node, and set the number of reconnection times to be increased by 1;

[0053] If so, an alarm message indicating that the migration is interrupted is output.

[0054] In order to solve the above technical problems, the present invention further provides a data migration device, comprising:

[0055] An acquisition module, used to acquire relevant information of each data to be migrated in the source node; wherein the relevant information at least includes access logs and attribute information;

[0056] A determination module, used to determine migration parameters of each of the data to be migrated according to the relevant information;

[0057] A judgment module, used for judging whether to allow the corresponding data to be migrated to be migrated according to each migration parameter; if so, triggering the migration module;

[0058] The migration module is used to migrate the data to be migrated from the source node to the target node.

[0059] In order to solve the above technical problems, the present invention further provides a data migration device, comprising:

[0060] Memory for storing computer programs;

[0061] A processor is used to implement the steps of the above-mentioned data migration method when executing the computer program.

[0062] In order to solve the above technical problem, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above data migration method are implemented.

[0063] The data migration method provided by the present invention obtains relevant information of each data to be migrated in the source node; wherein the relevant information at least includes access logs and attribute information; determines the migration parameters of each data to be migrated according to the relevant information; determines whether to allow the migration of the corresponding data to be migrated according to each migration parameter; and if so, migrates the data to be migrated from the source node to the target node.

[0064] The beneficial effect of the present invention is that when there is a need to reduce the capacity of a distributed database, instead of directly migrating the data to be migrated in the source node, the relevant information of the data to be migrated is obtained, and then the migration parameters of the data to be migrated are determined based on the relevant information, and this is used as the basis for data selection and migration to determine whether the corresponding data to be migrated is allowed to be migrated. Since the access log and attribute information respectively characterize the access situation of the data and the important and related situations of the data itself, the migration parameters generated according to the correlation information take into account the access situation, important and related situations of the data itself, which can make the migration decision more reasonable, and can accurately and effectively select data based on the migration parameters; if it is confirmed that the corresponding data to be migrated is allowed to be migrated, the data to be migrated is migrated from the source node to the target node, ensuring the timely migration of important data and improving system performance. The omission of important data or the migration of unnecessary data is avoided, so that the reduced system can better meet business needs.

[0065] On the other hand, the present invention specifically obtains the access time, visitor, access operation type and access content of the data to be migrated to obtain the access log of the data to be migrated; obtains the creation time, modification time, data type, data size and business domain information of the data to be migrated to obtain the attribute information of the data to be migrated; pre-processes the access log and attribute information, removes duplicate information in the access log and attribute information, and fills in the missing information in the access log and attribute information, thereby achieving the acquisition of the access log and attribute information and ensuring the integrity and accuracy of the access log and attribute information. The access frequency, importance information and correlation information of each data to be migrated are determined according to the relevant information, so that the importance of the data to be migrated and the degree of association with other data can be determined; based on at least one parameter of the access frequency, importance information and correlation information, it is judged whether the corresponding data to be migrated is allowed to be migrated, thereby ensuring the feasibility of data migration.

[0066] In addition, the present invention also provides a data migration device, equipment and medium, with the same effects as above. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0068] Figure 1 A flow chart of a data migration method provided by an embodiment of the present invention;

[0069] Figure 2 A schematic diagram of a data migration device provided by an embodiment of the present invention;

[0070] Figure 3 A schematic diagram of a data migration device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0071] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] The core of the present invention is to provide a data migration method, device, equipment and medium to solve the problem that the current data selection migration method in a distributed database is not intelligent enough, which may cause important data to fail to migrate in time or unnecessary data to be migrated, thereby affecting system performance.

[0073] In order to enable those skilled in the art to better understand the scheme of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0074] At present, in order to improve the resource utilization of distributed databases and reduce costs, distributed databases can be horizontally scaled down, that is, data and loads are redistributed to fewer nodes to adapt to business changes. Currently, horizontal scaling is mainly achieved by data selection and migration manually or based on simple rules (such as data creation time, modification time or size). However, this data selection method is not intelligent enough, which may cause important data to fail to migrate in time or unnecessary data to be migrated, thereby affecting system performance. For example, frequently accessed critical data may not be migrated first, resulting in a slower system response speed after scaling down. Therefore, in order to solve the above problems, the present invention provides a data migration method.

[0075] Figure 1 A flow chart of a data migration method provided by an embodiment of the present invention. Figure 1 As shown, the method includes:

[0076] S10: Obtain relevant information of each data to be migrated in the source node.

[0077] The relevant information at least includes access logs and attribute information.

[0078] Specifically, when horizontally scaling down a distributed database, it is first necessary to determine the source node in the distributed database. It is understandable that a distributed database is composed of multiple storage nodes; among the multiple storage nodes, the node whose data needs to be migrated is the source node. At the same time, it is also necessary to obtain relevant information about each data to be migrated in the source node.

[0079] It should be noted that the relevant information of the data to be migrated includes at least access logs and attribute information. Among them, the access log generally includes information such as the access time and visitor of the data; the attribute information generally includes information such as the creation time and modification time of the data. In this embodiment, there is no restriction on the specific content of the relevant information, and there is no restriction on the specific content of the access log and attribute information, which depends on the specific implementation situation.

[0080] S11: Determine migration parameters of each data to be migrated according to relevant information.

[0081] Furthermore, migration parameters of each data to be migrated are determined respectively according to the relevant information of each data to be migrated. It should be noted that the migration parameters are used as reference data to decide whether to migrate the data to be migrated. In this embodiment, there is no restriction on the specific content contained in the migration parameters. For example, it may include the result of whether the migration is allowed, the feasibility of migrating the data to be migrated, and some indicator information of the data to be migrated generated from the relevant information. In addition, in this embodiment, there is no restriction on the specific process of determining the migration parameters of the data to be migrated according to the relevant information, which depends on the specific implementation situation.

[0082] S12: judging whether the corresponding data to be migrated is allowed to be migrated according to each migration parameter; if so, proceeding to step S13.

[0083] S13: Migrate the data to be migrated from the source node to the target node.

[0084] Finally, it is determined whether the corresponding data to be migrated is allowed to be migrated according to the obtained migration parameters. It can be understood that the migration parameters are used as reference data to determine whether to migrate the data to be migrated. Therefore, if it is determined according to the obtained migration parameters that the corresponding data to be migrated is allowed to be migrated, the data to be migrated is directly migrated from the source node to the target node; if it is determined according to the obtained migration parameters that the corresponding data to be migrated is not allowed to be migrated, the data migration process is directly terminated.

[0085] It should be noted that the target node is the migration destination of the data to be migrated, and is one of the multiple storage nodes in the distributed database. In this embodiment, there is no limitation on the method of determining the target node, which depends on the specific implementation situation.

[0086] In this embodiment, when there is a need to reduce the capacity of a distributed database, the data to be migrated in the source node is not directly migrated, but the relevant information of the data to be migrated is obtained, and then the migration parameters of each data to be migrated are determined based on the relevant information, and this is used as the basis for data selection and migration to determine whether the corresponding data to be migrated is allowed to be migrated. Based on the migration parameters, data selection can be performed accurately and effectively; if it is confirmed that the corresponding data to be migrated is allowed to be migrated, the data to be migrated is migrated from the source node to the target node, ensuring the timely migration of important data and improving system performance. This avoids the omission of important data or the migration of unnecessary data, so that the reduced system can better meet business needs.

[0087] Based on the above embodiment, in some embodiments, obtaining relevant information of each data to be migrated in the source node includes:

[0088] S101: Obtain access time, accessor, access operation type and access content of the data to be migrated to obtain an access log of the data to be migrated;

[0089] Among them, the access operation types include query operation, update operation and delete operation;

[0090] S102: Acquire the creation time, modification time, data type, data size, and business domain information of the data to be migrated to obtain attribute information of the data to be migrated;

[0091] S103: pre-process the access log and the attribute information, remove duplicate information in the access log and the attribute information, and fill in the missing information in the access log and the attribute information.

[0092] In order to obtain the relevant information of each data to be migrated in the source node, in the specific implementation, it is first necessary to obtain the access time, visitor, access operation type and access content of the data to be migrated, so as to obtain the access log of the data to be migrated. It should be noted that the access operation type includes query operation, update operation and delete operation. For example, for query operation, it is necessary to record the query conditions and returned results, etc.; for update operation, it is necessary to record the updated fields and new values, etc.

[0093] Furthermore, the creation time, modification time, data type, data size and business domain information of the data to be migrated are obtained, so as to obtain the attribute information of the data to be migrated. For example, the data type of the data to be migrated includes integer type, string type and date type, etc.; the business domain information can be e-commerce field, financial field, medical field, etc.

[0094] In order to ensure the accuracy and completeness of access logs and attribute information, it is also necessary to preprocess the access logs and attribute information. Specifically, duplicate information in the access logs and attribute information is removed, and missing information in the access logs and attribute information is filled, so as to ensure the quality and consistency of the information, so that the migration parameters can be accurately obtained through the access logs and attribute information in the future.

[0095] In this embodiment, the access log of the data to be migrated is obtained by obtaining the access time, visitor, access operation type and access content of the data to be migrated; the creation time, modification time, data type, data size and business domain information of the data to be migrated are obtained to obtain the attribute information of the data to be migrated; the access log and attribute information are preprocessed to remove duplicate information in the access log and attribute information, and fill in the missing information in the access log and attribute information, thereby realizing the acquisition of the access log and attribute information and ensuring the integrity and accuracy of the access log and attribute information.

[0096] Based on the above embodiments, in some embodiments, the migration parameters of each data to be migrated are determined according to the relevant information, including:

[0097] S111: Determine the access frequency, importance information, and relevance information of each data to be migrated according to the relevant information;

[0098] Among them, the access frequency represents the number of times the data to be migrated is accessed per unit time; the importance information is the importance of the data to be migrated determined based on the business value, access frequency and update frequency of the data to be migrated; and the correlation information represents the degree of association between the data to be migrated.

[0099] In order to determine the migration parameters of the data to be migrated, in this embodiment, the access frequency, importance information and correlation information of each data to be migrated are determined respectively according to the relevant information. It should be noted that the access frequency represents the number of accesses to the data to be migrated per unit time; the importance information is the importance of the data to be migrated determined based on the business value, access frequency and update frequency of the data to be migrated; the correlation information represents the degree of association between the data to be migrated. The access frequency, importance information and correlation information are respectively used as reference data to decide whether to migrate the data to be migrated. In this embodiment, there is no limitation on the method of determining the access frequency, importance information and correlation information.

[0100] Correspondingly, whether the corresponding data to be migrated is allowed to be migrated is determined based on each migration parameter, and specifically, whether the corresponding data to be migrated is allowed to be migrated is determined based on at least one parameter among the access frequency, importance information, and correlation information. In other words, any one parameter among the access frequency, importance information, and correlation information can be selected as reference data to determine whether to migrate the data to be migrated; any two parameters among the access frequency, importance information, and correlation information can also be selected as reference data to determine whether to migrate the data to be migrated; and the access frequency, importance information, and correlation information can also be used together as reference data to determine whether to migrate the data to be migrated. In this embodiment, there is no limitation on the specific selection method of the migration parameters, which depends on the specific implementation situation.

[0101] In this embodiment, the access frequency, importance information and correlation information of each data to be migrated are determined respectively according to relevant information, so that the importance of the data to be migrated and the degree of association with other data can be determined; based on at least one parameter among the access frequency, importance information and correlation information, it is judged whether the migration of the corresponding data to be migrated is allowed, thereby ensuring the feasibility of data migration.

[0102] The following is a detailed description of the process of determining the three parameters of access frequency, importance information and relevance information in conjunction with a specific embodiment:

[0103] (1) Frequency of visits;

[0104] Based on the above embodiments, in some embodiments, determining the access frequency of the data to be migrated includes:

[0105] S112: Determine the data collection cycle;

[0106] S113: Determine the number of accesses to the data to be migrated within the data collection cycle;

[0107] S114: Determine the access frequency of the data to be migrated according to the data collection cycle and the number of times the data to be migrated is accessed within the data collection cycle.

[0108] In order to determine the access frequency of the data to be migrated, a data collection cycle is specifically determined, and the number of accesses of the data to be migrated within the data collection cycle is determined. In this embodiment, there is no restriction on the data collection cycle, which is determined according to the specific implementation situation.

[0109] Furthermore, the access frequency of the data to be migrated is determined according to the data collection cycle and the number of times the data to be migrated is accessed within the data collection cycle. The specific formula is as follows:

[0110] ;

[0111] in, For the The access frequency of the data to be migrated, For the Data to be migrated, is a positive integer, For the The number of accesses to the data to be migrated during the data collection cycle, The data collection cycle.

[0112] (2) information of importance;

[0113] Based on the above embodiments, in some embodiments, determining the importance information of the data to be migrated includes:

[0114] S115: Determine the business value of the data to be migrated according to the creation time, modification time, data type, data size, and business domain information of the data to be migrated;

[0115] S116: Determine the update frequency of the data to be migrated according to the creation time and modification time of the data to be migrated;

[0116] S117: Determine importance information of the data to be migrated according to the business value, access frequency, and update frequency of the data to be migrated.

[0117] In order to determine the importance of the data to be migrated, the business value of the data to be migrated is determined based on the creation time, modification time, data type, data size and business field information of the data to be migrated. It should be noted that the business value of the data to be migrated can be determined based on business needs and expert evaluation, and the value range is [0,1]; when the value is 0, the business value is the lowest, and when the value is 1, the business value is the highest.

[0118] Furthermore, the update frequency of the data to be migrated is determined according to the creation time and modification time of the data to be migrated. It can be understood that the update frequency represents the number of updates of the data to be migrated per unit time. Therefore, similar to the method of determining the access frequency, when determining the number of updates of the data to be migrated, a data collection cycle can also be determined, with the creation time of the data to be migrated as the data collection starting point, and the number of modifications of the data to be migrated determined according to the modification time of the data to be migrated within the data collection cycle. Finally, the quotient of the number of modifications and the data collection cycle is calculated to obtain the number of updates of the data to be migrated.

[0119] Finally, the importance of the data to be migrated is determined based on the business value, access frequency, and update frequency of the data to be migrated. The formula is as follows:

[0120] ;

[0121] in, For the The importance of the data to be migrated. For the The business value of the data to be migrated. For the The update frequency of the data to be migrated, For the The access frequency of the data to be migrated, are weight coefficients, .

[0122] (3) relevant information;

[0123] Based on the above embodiments, in some embodiments, determining the correlation information of the data to be migrated includes:

[0124] S118: Obtain observation values ​​of each data to be migrated respectively; wherein the observation values ​​are sample values ​​obtained by collecting the data to be migrated based on different conditions;

[0125] S119: Determine the number of observation values ​​of each data to be migrated;

[0126] S120: determining the observation average value corresponding to each data to be migrated according to the observation value and the number of observation values ​​corresponding to each data to be migrated;

[0127] S121: Determine the correlation information of each data to be migrated according to the observation value, the number of observation values ​​and the observation average value of each data to be migrated.

[0128] In order to determine the correlation information of the data to be migrated, the observation values ​​of each data to be migrated are obtained respectively. It should be noted that the observation value is a sample value obtained by collecting the data to be migrated based on different conditions, which can be extracted through the attribute information and access log of the data to be migrated; for example, the specific value obtained by collecting the data to be migrated based on different time points or specific circumstances, including data size, number of accesses, etc.

[0129] There are multiple observation values ​​of the data to be migrated, and the number of observation values ​​of each data to be migrated needs to be further determined, and the observation average value corresponding to each data to be migrated is determined according to the corresponding observation value and the number of observation values ​​of each data to be migrated. It should be noted that the observation average value is the sum of all observation values ​​divided by the number of observation values.

[0130] Finally, according to the observed value, number of observed values ​​and observed average value of each data to be migrated, the correlation information of each data to be migrated is determined. The specific formula is as follows:

[0131] ;

[0132] in, For the The data to be migrated and The correlation information of the data to be migrated. For the of data to be migrated Observations, For the of data to be migrated Observations, For the The average value of observations of the data to be migrated, For the The average value of observations of the data to be migrated, is the number of observations, .

[0133] In summary, the determination of the three parameters of access frequency, importance information and relevance information is achieved respectively.

[0134] Based on the above embodiments, in some embodiments, judging whether to allow the corresponding data to be migrated to be migrated according to each migration parameter includes:

[0135] S122: Determine whether the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the correlation information is not less than the third threshold; if it is confirmed that the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the correlation information is not less than the third threshold, then the corresponding data to be migrated is allowed to be migrated, otherwise the corresponding data to be migrated is not allowed to be migrated.

[0136] In a specific implementation, in order to accurately determine whether to allow the corresponding data to be migrated to be migrated, the three parameters of access frequency, importance information and relevance information are all used as the basis for determination, specifically determining whether the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the relevance information is not less than the third threshold. It should be noted that in this embodiment, there is no restriction on the first threshold, the second threshold and the third threshold, which are determined according to the specific implementation situation.

[0137] If it is confirmed that the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the relevance information is not less than the third threshold, the corresponding data to be migrated is allowed to be migrated, otherwise the corresponding data to be migrated is not allowed to be migrated. The specific relationship is as follows:

[0138] ;

[0139] in, is the data migration result, representing the Whether the data to be migrated is marked as data that needs to be migrated; Characterization The data to be migrated is marked as data that needs to be migrated, and migration is allowed. Characterization The data to be migrated is not marked as data that needs to be migrated, so migration is not allowed; is the first threshold, is the second threshold, is the third threshold.

[0140] In this embodiment, if it is confirmed that the access frequency is not less than the first threshold, and the importance information is not less than the second threshold, and the correlation information is not less than the third threshold, the corresponding data to be migrated is allowed to be migrated, otherwise the corresponding data to be migrated is not allowed to be migrated, thereby achieving accurate judgment on whether to migrate the data to be migrated, avoiding the omission of important data or the migration of unnecessary data, and enabling the reduced system to better meet business needs.

[0141] In order to reduce the migration time and resource consumption of the data to be migrated, based on the above embodiments, in some embodiments, migrating the data to be migrated from the source node to the target node includes:

[0142] S131: Obtain the load of each node in the distributed database and obtain the network bandwidth between each node;

[0143] S132: Obtain the data size of the data to be migrated;

[0144] S133: Determine the migration path cost of each migration path of the data to be migrated according to the load of each node, the network bandwidth between the nodes, and the data size of the data to be migrated;

[0145] S134: Determine a minimum migration path cost based on the costs of each migration path;

[0146] S135: Determine the migration path corresponding to the minimum migration path cost as the target migration path;

[0147] S136: Determine the node corresponding to the target migration path as the target node, and migrate the data to be migrated from the source node to the target node through the target migration path.

[0148] When migrating the data to be migrated, it is necessary to calculate the cost of each potential migration path based on factors such as network bandwidth and node load, and select the path with the lowest cost as the optimal migration path. Specifically, it is necessary to obtain the load of each node in the distributed database, the network bandwidth between each node, and the data size of the data to be migrated.

[0149] Further, according to the load of each node, the network bandwidth between each node, and the data size of the data to be migrated, the migration path cost of each migration path of the data to be migrated is determined. The specific formula is as follows:

[0150] ;

[0151] in, Migration Path The migration path cost, For slave nodes To Node The network bandwidth For Node The load, Data to be migrated The size of is the weight parameter.

[0152] Finally, the minimum migration path cost is determined based on the migration path costs, the migration path corresponding to the minimum migration path cost is determined as the target migration path, and the node corresponding to the target migration path is determined as the target node, so that the data to be migrated is migrated from the source node to the target node through the target migration path. In this way, the migration of the data to be migrated is completed.

[0153] In order to monitor the data migration progress and the system resource usage in real time during the migration process to ensure the smooth progress of the migration process, based on the above embodiments, in some embodiments, the method further includes:

[0154] S14: monitoring the performance index of the system processor during the migration of the data to be migrated through a preset command;

[0155] S15: monitoring the amount of migrated data during the migration of the data to be migrated, and monitoring the amount of used memory and used network bandwidth of the system during the migration of the data to be migrated;

[0156] S16: Determine the quotient of the amount of data that has been migrated and the total amount of data to be migrated and express it as a percentage to obtain the migration progress;

[0157] S17: Determine the quotient of the used memory amount and the total memory amount and express it as a percentage to obtain memory usage;

[0158] S18: Determine the quotient of the used network bandwidth and the total network bandwidth and express it as a percentage to obtain the network bandwidth usage;

[0159] S19: Outputs the migration progress, memory usage, and network bandwidth usage.

[0160] Specifically, the performance indicators of the system processor during the migration process of the data to be migrated are monitored through preset commands. For example, the system monitoring tool (TOP command) is used to continuously observe various performance indicators of the system during the data migration process, determine the load of the processor at different stages, and track the processor's clock cycle allocation, instruction execution frequency, and the working status of each core in real time to accurately evaluate the extent to which the processor resources are occupied by the data migration task, so that adjustment measures can be taken in time when the processor load is too high, such as optimizing the data migration strategy, adjusting the task priority, or increasing the allocation of system resources, etc., to ensure that the data migration process will not be stuck, delayed, or even fail due to excessive consumption of processor resources, thereby ensuring efficient and stable data migration.

[0161] The amount of data that has been migrated during the migration of the data to be migrated is further monitored, and the amount of memory used by the system and the amount of network bandwidth used during the migration of the data to be migrated are monitored. The quotient of the amount of data that has been migrated and the total amount of data to be migrated is determined and expressed as a percentage to obtain the migration progress. The formula is as follows:

[0162] ;

[0163] in, For migration progress, is the amount of data that has been migrated, The total amount of data to be migrated.

[0164] Determine the quotient of the used memory and the total memory and express it as a percentage to get the memory usage. The formula is as follows:

[0165] ;

[0166] in, For memory usage, is the amount of memory used, The total amount of memory.

[0167] Determine the quotient of the used network bandwidth and the total network bandwidth and express it as a percentage to obtain the network bandwidth usage. The formula is as follows:

[0168] ;

[0169] in, For network bandwidth usage, is the network bandwidth used, is the total network bandwidth.

[0170] Finally, the migration progress, memory usage, and network bandwidth usage are output, so that the data migration progress and system resource usage can be monitored in real time during the migration process to ensure the smooth progress of the migration process.

[0171] In order to process abnormal network interruption during the migration process, based on the above embodiments, in some embodiments, the method further includes:

[0172] S20: When a network interruption is detected during the migration of the data to be migrated, determine whether the number of reconnections between the source node and the target node reaches a threshold; if not, proceed to step S21; if yes, proceed to step S22;

[0173] S21: resend a connection request to the target node to reestablish the communication connection between the source node and the target node, and set the number of reconnection times to be increased by 1;

[0174] S22: Outputting alarm information indicating that the migration is interrupted.

[0175] In a specific implementation, when a network interruption is detected during the migration of the data to be migrated, it is determined whether the number of reconnections between the source node and the target node reaches a threshold. In this embodiment, there is no restriction on the threshold value, which is determined according to the specific implementation situation.

[0176] If it is confirmed that the number of reconnections between the source node and the target node has not reached the threshold, a connection request is resent to the target node to reestablish the communication connection between the source node and the target node, and the number of reconnections is set to be plus 1. If it is confirmed that the number of reconnections between the source node and the target node has reached the threshold, it is considered that the multiple reconnections between the nodes still fail, and the reconnection is stopped. An alarm message indicating the interruption of migration is output to remind the user to check and handle it in time. In this way, the abnormal network interruption during the migration process is handled.

[0177] In addition, after the data migration is completed, to ensure that the system can maintain good performance and stability under the new database architecture, the following detailed configuration and parameter adjustment steps are required:

[0178] Adjust database cache size: Re-evaluate and adjust the database cache size based on the new database architecture and data volume. An appropriate cache size can improve data read speed and overall system performance. If the amount of data decreases, the cache size can be appropriately reduced to save memory resources; if the data access pattern changes, the cache size may need to be increased to improve the hit rate.

[0179] Adjust the number of connection pools: The connection pool is used to manage database connections to reduce the overhead of establishing and closing connections. Adjust the number of connection pools based on the new database architecture and the expected concurrent access volume. If the concurrent access volume decreases, the number of connection pools can be appropriately reduced to save system resources; if the concurrent access volume increases, the number of connection pools may need to be increased to ensure that the system can handle more concurrent requests.

[0180] Update metadata information: Metadata is data that describes data, including information such as the data's storage location, structure, and type. After data migration is completed, metadata information needs to be updated to ensure that the system can accurately locate and access the new data location. This includes updating the table's storage location, column definitions, constraints, and other information.

[0181] Update index structure: Indexes are used to speed up data query and retrieval operations. After data migration is completed, the index structure needs to be evaluated and updated to ensure that it can adapt to the new data distribution and access mode. This may include creating new indexes, deleting indexes that are no longer needed, and adjusting the column order of indexes. By optimizing the index structure, data access efficiency can be improved and query time can be reduced.

[0182] Test and verify database performance: After completing configuration adjustments and metadata updates, conduct comprehensive testing and verification of the scaled-down database. This includes simulating actual business scenarios and testing indicators such as database read and write performance, query speed, and concurrent processing capabilities. Through testing, potential performance issues can be discovered and resolved to ensure that the system can meet business needs.

[0183] Optimization and adjustment: If any problems or performance bottlenecks are found during the test, timely adjustments and optimizations are required. This may include further adjustment of parameters such as cache size, number of connection pools, index structure, or code optimization, query optimization, etc. Through continuous optimization and adjustment, the performance and stability of the system can be improved to ensure that it can efficiently support the normal operation of the business.

[0184] Through the above steps, we can ensure that after the data migration is completed, the system can maintain good performance and stability under the new database architecture to meet business needs.

[0185] In the above embodiments, the data migration method is described in detail. The present invention also provides a corresponding embodiment of the data migration device.

[0186] Figure 2 Schematic diagram of a data migration device provided by an embodiment of the present invention. Figure 2 As shown, the device comprises:

[0187] The acquisition module 10 is used to acquire relevant information of each data to be migrated in the source node; wherein the relevant information at least includes access logs and attribute information.

[0188] The determination module 11 is used to determine the migration parameters of each data to be migrated according to the relevant information.

[0189] The judgment module 12 is used to judge whether the corresponding data to be migrated is allowed to be migrated according to each migration parameter; if so, the migration module 13 is triggered.

[0190] The migration module 13 is used to migrate the data to be migrated from the source node to the target node.

[0191] In some embodiments, the acquisition module 10 includes:

[0192] The first acquisition submodule is used to acquire the access time, visitor, access operation type and access content of the data to be migrated, so as to obtain the access log of the data to be migrated; wherein the access operation type includes query operation, update operation and delete operation;

[0193] The second acquisition submodule is used to acquire the creation time, modification time, data type, data size and business domain information of the data to be migrated, so as to obtain the attribute information of the data to be migrated;

[0194] The preprocessing module is used to preprocess the access log and attribute information, remove duplicate information in the access log and attribute information, and fill in the missing information in the access log and attribute information.

[0195] In some embodiments, the determination module 11 includes:

[0196] The parameter determination submodule is used to determine the access frequency, importance information and relevance information of each data to be migrated according to the relevant information;

[0197] Among them, the access frequency represents the number of accesses to the data to be migrated per unit time; the importance information is the importance of the data to be migrated determined based on the business value, access frequency and update frequency of the data to be migrated; the correlation information represents the degree of association between the data to be migrated;

[0198] Correspondingly, the determination module 12 determines whether to allow the migration of the corresponding data to be migrated according to at least one parameter among the access frequency, the importance information and the correlation information.

[0199] In some embodiments, the parameter determination submodule includes:

[0200] A first determination submodule is used to determine a data collection period;

[0201] The second determination submodule is used to determine the number of accesses to the data to be migrated within a data collection period;

[0202] The third determination submodule is used to determine the access frequency of the data to be migrated according to the data collection period and the number of times the data to be migrated is accessed within the data collection period.

[0203] In some embodiments, the parameter determination submodule includes:

[0204] The fourth determination submodule is used to determine the business value of the data to be migrated according to the creation time, modification time, data type, data size and business domain information of the data to be migrated;

[0205] A fifth determination submodule, used to determine the update frequency of the data to be migrated according to the creation time and modification time of the data to be migrated;

[0206] The sixth determination submodule is used to determine the importance information of the data to be migrated according to the business value, access frequency and update frequency of the data to be migrated.

[0207] In some embodiments, the parameter determination submodule includes:

[0208] The third acquisition submodule is used to respectively acquire the observation value of each data to be migrated; wherein the observation value is a sample value obtained by collecting the data to be migrated based on different conditions;

[0209] The seventh determination submodule is used to determine the number of observation values ​​of each data to be migrated;

[0210] An eighth determination submodule, used to determine the observed average value corresponding to each data to be migrated according to the observed value and the number of observed values ​​corresponding to each data to be migrated;

[0211] The ninth determination submodule is used to determine the correlation information of each data to be migrated according to the observation value, the number of observation values ​​and the observation average value of each data to be migrated.

[0212] In some embodiments, the determination module 12 includes:

[0213] The first judgment submodule is used to judge whether the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the correlation information is not less than the third threshold; if it is confirmed that the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the correlation information is not less than the third threshold, then the corresponding data to be migrated is allowed to be migrated, otherwise the corresponding data to be migrated is not allowed to be migrated.

[0214] In some embodiments, the migration module 13 includes:

[0215] The fourth acquisition submodule is used to obtain the load of each node in the distributed database and obtain the network bandwidth between each node;

[0216] The fifth acquisition submodule is used to acquire the data size of the data to be migrated;

[0217] A tenth determination submodule, used to determine the migration path cost of each migration path of the data to be migrated according to the load of each node, the network bandwidth between the nodes, and the data size of the data to be migrated;

[0218] An eleventh determination submodule is used to determine a minimum migration path cost based on each migration path cost;

[0219] A twelfth determination submodule, used to determine the migration path corresponding to the minimum migration path cost as the target migration path;

[0220] The migration submodule is used to determine the node corresponding to the target migration path as the target node, and migrate the data to be migrated from the source node to the target node through the target migration path.

[0221] In some embodiments, it also includes:

[0222] The first monitoring module is used to monitor the performance index of the system processor during the migration of the data to be migrated through a preset command;

[0223] The second monitoring module is used to monitor the amount of migrated data during the migration of the data to be migrated, and to monitor the amount of used memory and used network bandwidth of the system during the migration of the data to be migrated;

[0224] A migration progress determination module is used to determine the quotient of the amount of data that has been migrated and the total amount of data to be migrated and express it as a percentage to obtain the migration progress;

[0225] A memory usage determination module is used to determine the quotient of the used memory amount and the total memory amount and express it as a percentage to obtain the memory usage;

[0226] A network bandwidth usage determination module is used to determine the quotient of the used network bandwidth and the total network bandwidth and express it as a percentage to obtain the network bandwidth usage;

[0227] Output module, used to output migration progress, memory usage, and network bandwidth usage.

[0228] In some embodiments, it also includes:

[0229] The second judgment submodule is used to judge whether the number of reconnection times between the source node and the target node reaches a threshold when a network interruption is detected during the migration process of the data to be migrated; if not, a connection request is resent to the target node to re-establish the communication connection between the source node and the target node, and the number of reconnections is set to be plus 1; if so, an alarm message indicating the migration interruption is output.

[0230] Since the embodiments of the apparatus part correspond to the embodiments of the method part, please refer to the description of the embodiments of the method part for the embodiments of the apparatus part, which will not be repeated here.

[0231] In addition, the present invention also provides a computer program product, including a computer program or instructions, which implement the steps of the above-mentioned data migration method when executed by a processor.

[0232] Figure 3 A schematic diagram of a data migration device provided by an embodiment of the present invention. Figure 3 As shown, the data migration device includes:

[0233] A memory 20, used for storing computer programs;

[0234] The processor 21 is used to implement the steps of the data migration method mentioned in the above embodiment when executing the computer program.

[0235] The data migration device provided in this embodiment may include but is not limited to a smart phone, a tablet computer, a laptop computer, or a desktop computer.

[0236] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of a digital signal processor (DSP), a field programmable gate array (FPGA), and a programmable logic array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 21 may be integrated with a graphics processing unit (GPU), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an artificial intelligence (AI) processor, which is used to process computing operations related to machine learning.

[0237] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein, after the computer program is loaded and executed by the processor 21, it can implement the relevant steps of the data migration method disclosed in any of the aforementioned embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, etc., and the storage method may be temporary storage or permanent storage. Among them, the operating system 202 may include Windows, Unix, Linux, etc. Data 203 may include but is not limited to data involved in the data migration method.

[0238] In some embodiments, the data migration device may further include a display screen 22 , an input / output interface 23 , a communication interface 24 , a power supply 25 , and a communication bus 26 .

[0239] Those skilled in the art will understand that Figure 3 The structure shown in the figure does not constitute a limitation on the data migration device, and may include more or fewer components than those shown in the figure.

[0240] Finally, the present invention also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps recorded in the above method embodiment are implemented.

[0241] It is understandable that if the method in the above embodiment is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc. Various media that can store program codes.

[0242] The above is a detailed introduction to a data migration method, device, equipment and medium provided by the present invention. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referenced to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present invention, the present invention can be improved and modified in several ways, and these improvements and modifications also fall within the scope of protection of the present invention.

[0243] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

Claims

1. A data migration method, characterized in that: include: Obtain relevant information of each data to be migrated in the source node; wherein the relevant information at least includes access logs and attribute information; Determine migration parameters of each of the data to be migrated according to the relevant information; Determining whether to allow migration of the corresponding data to be migrated according to each migration parameter; If so, the data to be migrated is migrated from the source node to the target node.

2. The data migration method according to claim 1, characterized in that: Obtain relevant information about each data to be migrated in the source node, including: Acquire the access time, accessor, access operation type and access content of the data to be migrated to obtain the access log of the data to be migrated; wherein the access operation type includes query operation, update operation and delete operation; Acquire the creation time, modification time, data type, data size and business domain information of the data to be migrated to obtain the attribute information of the data to be migrated; The access log and the attribute information are preprocessed to remove duplicate information in the access log and the attribute information, and to fill in missing information in the access log and the attribute information.

3. The data migration method according to claim 2, characterized in that: Determining migration parameters of each of the to-be-migrated data respectively according to the relevant information includes: Determine the access frequency, importance information and relevance information of each of the to-be-migrated data respectively according to the relevant information; The access frequency represents the number of accesses to the data to be migrated per unit time; the importance information is the importance of the data to be migrated determined based on the business value of the data to be migrated, the access frequency and the update frequency; the correlation information represents the degree of association between the data to be migrated; Correspondingly, judging whether to allow migration of the corresponding data to be migrated according to each migration parameter includes: Whether to allow migration of the corresponding data to be migrated is determined according to at least one parameter among the access frequency, the importance information and the correlation information.

4. The data migration method according to claim 3, characterized in that: Determining the access frequency of the data to be migrated includes: Determine the data collection cycle; Determine the number of times the data to be migrated is accessed within the data collection period; The access frequency of the data to be migrated is determined according to the data collection cycle and the number of times the data to be migrated is accessed within the data collection cycle.

5. The data migration method according to claim 3, characterized in that: Determining the importance information of the data to be migrated includes: Determining the business value of the data to be migrated according to the creation time, the modification time, the data type, the data size and the business domain information of the data to be migrated; Determining an update frequency of the data to be migrated according to the creation time and the modification time of the data to be migrated; The importance information of the data to be migrated is determined according to the business value, the access frequency, and the update frequency of the data to be migrated.

6. The data migration method according to claim 3, characterized in that: Determining the correlation information of the data to be migrated includes: Obtaining observation values ​​of each of the data to be migrated respectively; wherein the observation values ​​are sample values ​​obtained by collecting the data to be migrated based on different conditions; Determining the number of observations of each of the data to be migrated; Determine the observed average value corresponding to each of the data to be migrated according to the observed value corresponding to each of the data to be migrated and the number of observed values; The correlation information of each of the data to be migrated is determined according to the observed value, the number of observed values ​​and the observed average value of each of the data to be migrated.

7. The data migration method according to claim 3, characterized in that: Judging whether to allow migration of the corresponding data to be migrated according to each migration parameter includes: Determining whether the access frequency is not less than a first threshold, the importance information is not less than a second threshold, and the relevance information is not less than a third threshold; If it is confirmed that the access frequency is not less than the first threshold, the importance information is not less than the second threshold, and the relevance information is not less than the third threshold, the corresponding data to be migrated is allowed to be migrated, otherwise the corresponding data to be migrated is not allowed to be migrated.

8. The data migration method according to any one of claims 1 to 7, characterized in that: Migrating the data to be migrated from the source node to the target node includes: Obtaining the load of each node in the distributed database and obtaining the network bandwidth between each of the nodes; Obtaining the data size of the data to be migrated; Determining a migration path cost of each migration path of the data to be migrated according to the load of each node, the network bandwidth between each node, and the data size of the data to be migrated; Determining a minimum migration path cost based on each of the migration path costs; Determining the migration path corresponding to the minimum migration path cost as the target migration path; A node corresponding to the target migration path is determined as the target node, and the data to be migrated is migrated from the source node to the target node through the target migration path.

9. The data migration method according to claim 8, characterized in that: Also includes: Monitoring the performance index of the system processor during the migration of the data to be migrated through a preset command; Monitoring the amount of data that has been migrated during the migration of the data to be migrated, and monitoring the amount of memory used and the network bandwidth used by the system during the migration of the data to be migrated; Determine the quotient of the amount of migrated data and the total amount of data to be migrated and express it as a percentage to obtain the migration progress; Determine the quotient of the used memory amount and the total memory amount and express it as a percentage to obtain memory usage; Determine the quotient of the used network bandwidth and the total network bandwidth and express it as a percentage to obtain network bandwidth usage; The migration progress, the memory usage and the network bandwidth usage are output.

10. The data migration method according to claim 8, characterized in that: Also includes: When a network interruption is detected during the migration of the data to be migrated, determining whether the number of reconnections between the source node and the target node reaches a threshold; If not, resend a connection request to the target node to reestablish the communication connection between the source node and the target node, and set the number of reconnection times to be increased by 1; If so, an alarm message indicating that the migration is interrupted is output.

11. A data migration device, characterized in that: include: An acquisition module, used to acquire relevant information of each data to be migrated in the source node; wherein the relevant information at least includes access logs and attribute information; A determination module, used to determine migration parameters of each of the data to be migrated according to the relevant information; A judgment module, used for judging whether to allow the corresponding data to be migrated to be migrated according to each migration parameter; if so, triggering the migration module; The migration module is used to migrate the data to be migrated from the source node to the target node.

12. A data migration device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the data migration method according to any one of claims 1 to 10 when executing the computer program.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the data migration method according to any one of claims 1 to 10 are implemented.

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